Abstract:The fault monitoring and location wavelet algorithm in the existing literature is carried out on the premise of the same recording frequency, and the real time detection of the small current grounding fault in the distribution network is completely different from the grounding fault detection environment of the substation: the distribution network fault monitoring device uses the different standard sampling frequency (3600Hz, 4800Hz) to send the real time fault record. Wave data to the distribution network center, more use 4096Hz sampling frequency to send fault recorded wave data, in the distribution network center needs to analyze and calculate the recording data of different sampling frequencies, extract fault features, detect faults, determine the head end of the fault, and realize fault detection and positioning. This paper gives the definition of the wavelet energy characteristics, the conversion of different sampling frequency energy characteristics, and the ground fault monitoring and positioning algorithm based on the energy characteristics in the distribution network. The fault detection and location of the grounding fault in the distribution network at various sampling frequencies, the energy characteristics of the fault energy are extracted by the wavelet transform, and the energy characteristics of the fault recording signals of different sampling frequencies are converted to the lowest sampling frequency. then according to the characteristics of energy to determine the fault type, fault to determine the head and tail end. Wavelet energy feature conversion algorithm based on multi sampling frequency is also useful for similar applications of wavelet transform.